Advanced Loop Optimizations in Compilers: Techniques and Challenges
This lecture delves into advanced loop optimization techniques critical for compiler design. Key topics include static single assignment (SSA) form optimizations, constant propagation, dead code elimination, loop invariant code motion, and various strategies for optimizing loops such as induction variable analysis, linear test replacement, loop unrolling, and scalar replacement. Each technique is illustrated with examples to demonstrate their practical application and potential performance benefits, while also discussing the limitations and challenges associated with these optimizations.
Advanced Loop Optimizations in Compilers: Techniques and Challenges
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Presentation Transcript
Advanced CompilersCMPSCI 710Spring 2003Basic Loop Optimizations Emery Berger University of Massachusetts, Amherst
Topics • Last time • Optimizations using SSA form • Constant propagation & dead code elimination • Loop invariant code motion • This time • Loop optimizations • Induction variable • Linear test replacement • Loop unrolling • Scalar replacement
Easy Detectionof Loop Induction Variables • Pattern match & check: • Search for “i = i + b” in loop • i is induction variable if no other assignment to i in loop • Pros & Cons: • Easy! • Does not catch all loop induction variablese.g., “i = a * c + 2”
Taxonomy of Induction Variables • basic induction variable: • only definition in loop is assignmentj = j § c, where c is loop invariant • mutual induction variable: • definition is linear function of other induction variable i‘: • i = c1 * i‘§ c2 • i = i‘ / c1 § c2 • family of basic induction variable j: • set of induction variables i such that i is always assigned linear function of j
Strength Reduction • Replace “expensive” op by “cheaper” one • E.g., replace multiply by addition • Apply to induction variable families • Especially: array indexing
Strength Reduction Algorithm • Let i be induction variable in the family of basic induction variable j: • i = c1 * j + c2 • Create new variable i’ • Initialize in pre-header: i’ = c1*j + c2 • Track value of j: after j = j + c3, add i’ = i’ + (c1 * c3)
Candidates for Strength Reduction • Induction variable IV multiplied by invariant • Recursively: • IV * IV, IV mod constant, IV + IV
Strength Reduction Examples • basic induction variable: • only definition in loop is assignmentj = j § c, where c is loop invariant • mutual induction variable: • definition is linear function of other induction variable i‘: • i = c1 * i‘§ c2 • i = i‘ / c1 § c2 • family of basic induction variable j: • set of induction variables i such that i is always assigned linear function of j
Linear Test Replacement • Eliminates induction variable! • After strength reduction, loop test is often last use of induction variable • Algorithm: • If only use of IV is loop test and its own increment, and test is always computed • i.e., only one exit from loop • Replace test with equivalent one: • E.g., “i comp k” ) “i_50 comp k*50”
Loop Unrolling • To reduce loop overhead, we can unroll loops • Advantages: • Execute fewer total instructions • More fodder for common subexpression elimination, strength reduction, etc. • Move consecutive access closer together • Disadvantages: • Code bloat • Still updating through memory
Scalar Replacement • Problem: register allocators never keep a[i] in register • Idea: trick allocator • Locate patterns of consistent reuse • Replace load with copy into temporary • Replace store with copy from temporary • May need copies at end of loop • E.g., when reuse spans > 1 iteration • Advantages: • Decreases number of loads and stores • Keeps reused values in registers • Big performance impact (2x, 3x!)
Scalar Replacement Example • Scalar replacement exposes the reuse of a[i] • Traditional scalar analysis – inadequate • Use dependence analysis to understand array references (later)
Next Time • Common Subexpression Elimination • Read ACDI: • Ch. 12, pp. 343-355 • Ch. 13, pp. 378-396
